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Cited by 768

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Camouflage and Display for Soft Machines

Open access
Morin, Stephen A., Shepherd, Robert F., Kwok, Sen Wai, Stokes, Adam A., Nemiroski, Alex, Whitesides, George M.·2012·Science

Abstract

Mechanical Chameleon: A wide range of animals can adapt their color patterns as a means of camouflage or otherwise changing their appearance. This is accomplished through changes in coloration, contrast, patterning, or shape. Morin et al. (p. 828 ) show at a basic level that some of these features can be added as microfluidic layers attached to mobile, flexible, soft machines. By pumping different fluids through the channels, the robots were able to change their coloration or overall contrast and could thus blend into the background of the surface they were lying upon. Conversely, by pumping through fluids of different temperature, the infrared profile of the robot could be changed without changing its visible coloration.

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Registry

Crossref · 10.1126/science.1222149

Cites

2 of 2 references verified0 citation errors · 0 not checkable

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Metadata

Authors
Morin, S. A., Shepherd, R. F., Kwok, S. W., Stokes, A. A., Nemiroski, A., & Whitesides, G. M.
Venue
Science
Published
2012-08-17
Volume
337
Issue
6096
Pages
828-832
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2101132776
Cited by
768
References
2
FWCI
52.92
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Camouflage and Display for Soft Machines. https://app.cochat.ai/papers/10.1126/science.1222149
The paper
Morin, S. A., Shepherd, R. F., Kwok, S. W., Stokes, A. A., Nemiroski, A., & Whitesides, G. M. (2012). Camouflage and Display for Soft Machines. Science. https://doi.org/10.1126/science.1222149

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.